Decompose territorial N losses by reference period (chained) — decompose_terr_losses

Runs the same four compartments as decompose_terr_losses(), but comparing each reference period (each averaged across its ten years) against the immediately preceding one — 1860-1870 -> 1920-1930 -> 1960-1970 -> 2010-2020 — plus one extra transition spanning the full analysis window, 1860-1870 straight to 2010-2020 (the total change), instead of chaining year on year. This is the periodised table recommended alongside the main chained figure in the decomposition proposal (section 12), summarizing the four historical phases rather than following the full 160-year trajectory.

Usage

decompose_terr_losses_periods(
  n_prov_destiny = NULL,
  raw = NULL,
  example = FALSE
)

Arguments

n_prov_destiny: Nitrogen flows tibble from create_n_prov_destiny(), shared across all four compartments. If NULL, loaded automatically.
raw: Named list overriding any of the raw inputs shared across compartments (npp_ygpit, codes_coefs, intake_ygiac, n_excretion_ygs, stock_prod_ygps, livestock_units, population_yg). Missing elements are loaded automatically.
example: If TRUE, return a small hardcoded output without downloading remote data. Default is FALSE.

Value

A named list with tibbles detail (per-compartment LMDI output, with compartment and mechanism columns added), by_compartment, and by_mechanism (each with period — one of "1865-1925", "1925-1965", "1965-2015", "Total (1865-2015)", the mean year of each reference window (1865 = mean of 1860-1870, and so on) — plus contribution_mgn, period_years, and contribution_per_yr_mgn, the per-year-normalized value used for plotting).

Examples

decompose_terr_losses_periods(example = TRUE)
#> $detail
#> # A tibble: 8 × 6
#>   period    factor_label           component_type additive compartment mechanism
#>   <chr>     <chr>                  <chr>             <dbl> <chr>       <chr>    
#> 1 1860-1920 Size                   factor           33253. cropland    Size     
#> 2 1860-1920 Intensity              factor           16268. cropland    Intensif…
#> 3 1860-1920 Inefficiency           factor          -53899. cropland    Ineffici…
#> 4 1860-1920 Cropland N surplus     target           -4379. cropland    Total    
#> 5 1860-1920 Size                   factor          -15150. semi_natur… Size     
#> 6 1860-1920 Intensity              factor            9236. semi_natur… Intensif…
#> 7 1860-1920 Inefficiency           factor           53368. semi_natur… Ineffici…
#> 8 1860-1920 Semi-natural N surplus target           47454. semi_natur… Total    
#> 
#> $by_compartment
#> # A tibble: 8 × 5
#>   period compartment  contribution_mgn period_years contribution_per_yr_mgn
#>    <dbl> <chr>                   <dbl>        <dbl>                   <dbl>
#> 1      1 cropland               -4379.           60                   -73.0
#> 2      2 cropland              395464            40                  9887. 
#> 3      1 semi_natural           47454.           60                   791. 
#> 4      2 semi_natural          163739            40                  4093. 
#> 5      1 manure                 -1649.           60                   -27.5
#> 6      2 manure                 33043.           40                   826. 
#> 7      1 urban                  62451.           60                  1041. 
#> 8      2 urban                  33567            40                   839. 
#> 
#> $by_mechanism
#> # A tibble: 6 × 5
#>   period mechanism       contribution_mgn period_years contribution_per_yr_mgn
#>    <dbl> <chr>                      <dbl>        <dbl>                   <dbl>
#> 1      1 Size                      80496.           60                  1342. 
#> 2      1 Intensification           25861.           60                   431. 
#> 3      1 Inefficiency              -2601.           60                   -43.3
#> 4      2 Size                      39875.           40                   997. 
#> 5      2 Intensification          364865            40                  9122. 
#> 6      2 Inefficiency             221223            40                  5531. 
#>